Multi-Objective Bayesian Optimization for Laminate-Inspired Mechanically Reinforced Piezoelectric Self-Powered Sensing Yarns.

ABSTRACT: Piezoelectric fiber yarns produced by electrospinning offer a versatile platform for intelligent devices, demonstrating mechanical durability and the ability to convert mechanical strain into electric signals. While conventional methods involve twisting a single poly(vinylidene fluoride-co-trifluoroethylene)(P(VDF-TrFE)) fiber mat to create yarns, by limiting control over the mechanical properties, an approach inspired by composite laminate design principles is proposed for strengthening. By stacking multiple electrospun mats in various sequences and twisting them into yarns, the mechanical properties of P(VDF-TrFE) yarn structures are efficiently optimized. By leveraging a multi-objective Bayesian optimization-based machine learning algorithm without imposing specific stacking restriction

SUBMITTER: Yang Z 

PROVIDER: S-EPMC11434127 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature